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The service environment of urban polyethylene (PE) pipes has a crucial influence on their long-term safety and performance. Based on the application and structural performance analysis of PE pipe failure cases, this study aims to investigate the impact of organic substances in the soil on the aging behavior of PE pipes by designing organic solutions with different concentrations, which are based on the composition of organic substances in the soil environment, and periodic immersion tests.

Soil samples in the vicinity of the failed pipes were analyzed by gas chromatography-mass spectrometry, sensitive organic substances were screened and soaking solutions of different concentrations were designed. After the soaking test, the PE pipe samples were analyzed using differential scanning calorimetry, Fourier-transform infrared spectroscopy and other testing methods.

The performance difference between the outer surface and the middle of the cross section of PE pipes highlights the influence of the soil service environment on their aging. Different organic solutions can have varying impacts on the aging behavior of PE pipes when immersed. For instance, when exposed to amine organic solutions, PE pipes may have an increased weight and decreased material yield strength, although there is no reduction in their thermal or oxygen stability. On the contrary, when subjected to ether organic solutions, the surface of PE pipe specimens may be affected, leading to a reduction in material fracture elongation and a decrease in their thermal and oxygen stability. Furthermore, immersion in either amine or ether organic solutions may result in the production of hydroxyl and other aging groups on the surface of the material.

Understanding the potential impact of organic substances in the soil environment on the aging of PE pipe ensures the long-term performance and safety of urban PE pipe. This research approach will provide valuable insights into improving the durability and reliability of urban PE pipes in soil environments.

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

During metro construction using the shield method, the construction process's complexity, the construction environment's variability, and other factors can easily lead to tunnel construction accidents. This paper aims to explore the interconnections between risk factors and related accident types, as well as the risk chain formed between risk factors, and to analyze the key risk factors and vulnerabilities in shield tunnel construction through empirical data.

Based on the social network analysis theory, the connection of various risk factors in subway shield tunnel construction is explored, and the mechanism of multiple risk factors is studied. Through literature analysis, articles on safety risk factors in metro shield tunnel construction are organized and studied, and the identified safety risk factors can comprehensively reflect the significant risks that need to be concerned in metro shield tunnel construction.

The results show that a small world characterizes the SNA network of safety risk factors for metro shield tunnel construction: The frequency of association between the five risk factors “unsafe behavior,” “site management,” “safety supervision and inspection,” “safety education system” and “safety protection” is higher than that of other factors. Only a few risks, such as “site management,” “safety supervision and inspection,” and “rapid response capability,” directly lead to accidents. In addition, risk factors such as the “safety education system” and “safety protection” will indirectly cause unsafe behaviors of construction personnel.

During construction, the probability of occurrence of risk factors may vary with the construction phase and area and is not considered in this paper. In addition, although this paper identifies, determines and analyzes the risk factors affecting the safety of metro shield tunnel construction, including the importance of each risk factor and the connection between them, more detailed information before and after the accident could not be obtained based on the accident investigation report alone. Therefore, future research can collect the same accident case from more sources to obtain more information.

The theory of accident causation has been improved at the theoretical level. The identified safety risk factors can comprehensively reflect the significant risks that need to be paid attention to in metro shield tunnel construction. From a practical point of view, the results of the study provide a basis for the rational control of the risk factors in the construction of subway shield tunnels, which can help guide practitioners to do a good job of risk prevention before the construction of metro shield tunnels and reduce the probability of related accidents.

This study expands the application of social network analysis in the field of subway tunnel construction risk, quantitatively analyzes the key risk factors and vulnerabilities in shield method tunnel construction and proposes policy recommendations for future metro tunnel construction safety management.

The purpose of this study is to investigate the influence of green finance on human well-being in China in the context of urbanization and aging population. It aims to explore the contributions of green finance in such demographic scenarios.

This study innovates and optimizes the calculation of the carbon intensity of human well-being (CIWB) index and strengthens the integrity of the assessment model for green finance development. It uses the serial multiple mediator model and moderation effect analysis to address the impact of green finance on human well-being in China on the provincial level from 2009 to 2020.

Green finance has a significant, positive and direct impact on human well-being. Simultaneously, it influences human well-being indirectly through three transmission channels. Urbanization and an ageing population are significant individual mediators through which green finance contributes to human well-being improvement. Notably, these two mediators also work together to transfer the promotional impact of green finance to human well-being.

The government can perfect the regulations to strengthen the market ecosystem to accelerate the development of green finance. Reforms on the administrative division to expand the size of cities with the implementation of ageing friendly development strategy is also necessary. Attracting incoming foreign direct investment in sustainable projects and adjusting public projects and trade activities to fulfil the sustainable principles are also regarded as essential.

The findings challenge traditional views on the impact of aging populations, highlighting the beneficial role of green finance in improving well-being amidst demographic changes. This offers a new perspective on economic and environmental sustainability in aging societies.

A multi-dimensional well-being indicator, CIWB and the serial multiple mediator model are used and direct and indirect impacts of green finance on human well-being is exhibited. It offers novel insights on the transmission channels behind, identifies the mediating role of urbanization and ageing population and offers empirical evidences with strong academic and policy implications.

Attentional bias toward safety (ABS) is a positive safety cognitive ability that could encourage individuals to engage in proactive safety behaviors; however, there is a lack of systematic sorting out of the driving mechanism of ABS. This study aims to identify the influencing factors and underlying mechanisms of ABS among construction workers (CWs) in China, thereby enhancing the practice of construction safety management.

An exploratory study using the open-ended approach of grounded theory was conducted, including 25-depth interviews with CWs. Based on the interviews’ records, a scale for measuring CWs’ ABS was developed and an empirical study on 554 workers was performed. The ABS scale was validated in conjunction with an ABS modification training experiment published by the authors’ team, and the theoretical model of the driving mechanism of CWs’ ABS was obtained.

The results showed that the six driving factors of construction workers’ ABS include organizational factors, risk perception, safety awareness, safety investment, job stress and workers’ educational level. This paper also identified the critical approach to improving workers’ ABS as an effective intervention on risk perception. In addition, the ABS scale was found to be effective in measuring the ABS level.

This paper is of importance in reducing the unsafe behaviors of construction workers and preventing and promoting the sustainable development of construction enterprises.

The purpose of this paper is to study the impact of different types of textures on the friction lubrication performance of cylindrical roller bearings.

In the present study, the composite texture hydrodynamic lubrication model that takes into account the effects of surface roughness is established, and the Reynolds equation for the oil film is numerically solved using the finite difference method. The study investigates the oil film carrying capacity and maximum pressure of bearings under two different arrangements of four composite textures and conducts a comparative analysis of the oil film characteristics under various texture parameters and surface roughness levels.

When the roughness of the inner texture surface and the contact surface are equal, the bearing capacity of the composite texture is intermediate between the two textures. The impact trend of surface roughness on fluid dynamic pressure effects varies with the type of composite texture; the internal roughness of the texture affects the micro-hydrodynamic pressure action. Composite textures with different depths exhibit improved bearing capacities; elliptical cylindrical parallel and elliptical hemispherical parallel textures perform better when their area densities are similar, while other types of composite textures show enhanced bearing performance as the ratio of their area densities increases.

This paper contributes to the theoretical investigations and analyses on designing the textured rolling bearings with high lubrication performance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0050

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

This study aims to evaluate the impact of several factors on the continuance participation intention of service providers in the sharing economy business model, i.e. food delivery application (FDA) service.

Based on primary data collected from 282 service providers, this study used partial least squares structural equation modeling (PLS-SEM) to validate measurement scales and the proposed model.

The SEM analysis revealed that service providers’ intention to continue participating was influenced by perceived social benefit, perceived economic benefit and the corporate image of the service enabler. Notably, the relationship between perceived social benefit and continuance participation intention is moderated by the service enabler’s corporate image. Furthermore, this study identified four antecedents that impact on perceived benefit of service providers, namely, market attractiveness, and marketing capabilities of service enabler, delivery quality and customers’ positive affective response. However, the effect of marketing capabilities of the service enabler on perceived economic benefit was found to be irrelevant.

This study enriches the authors’ understanding of the factors that promote service providers’ intention to continue participating in the sharing economy business model, particularly within the context of FDAs. Based on the findings, the study offers both theoretical and practical implications for service enablers, policymakers and technology providers to enhance stakeholder engagement in the sharing economy business model.

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.

Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.

The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.

Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.

In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.